Giovani in un'ora - Ciclo di seminari - Seconda parte

Day - Time: 11 March 2021, h.11:00
Place: Area della Ricerca CNR di Pisa - Room: Zoom

Fabio Carrara


Francesco Laccone - Computational design and behavior of FlexMaps architectures

Abstract: Bending-active techniques are known since ancient times, but only in recent years the interest on the topic is renewed thanks to the increase of computational power and the advent of digital fabrication technologies. A lot of methods are nowadays available (Lienhard et al. 2013), however they offer little or no shape control to the designer. FlexMaps (Malomo et al. 2017) is one of the few works (with La Magna 2017, and Panetta et al. 2019) that instead make it possible to impose a predefined target shape and search for the best configuration of the load-bearing elements, which once deformed result close enough to the target shape. FlexMaps has been revisited to work with complex-shaped lightweight architectures and a new pipeline has been introduced to manage all the design steps from shape conception to fabrication. This pipeline has been tested on two exemplary cases that use a common building material such as plywood. Here, digital fabrication through CNC milling is employed. The patches are fabricated with few human assistance and post-processing, and are assembled by-hand by bending and progressively connecting each other. Moreover, few scaffolding are needed and no shape control is required since the final shape of the structure automatically pops up once all patches are connected. One of the greatest novelty expressed by the FlexMaps Pavilion is that no hard restrictions are made on the target shape,l eading to an unparalleled design freedom with respect to state-of-the-art competitors. In general, the FlexMaps technique can be used whenever a nonstandard curved shape is needed, such as in shelters or facades and asformworks. This approach has a great potential in architecture as it can be scaled to larger structures, providing excellent shape expressiveness implying common material.

Nicola Messina - Towards Effective and Efficient Cross-Modal Visual Textual Retrieval

Abstract: Cross-modal visual-textual retrieval is an essential functionality in modern search engines, as it enables to search images using sentences written in natural language as queries and vice-versa. Current computer vision literature reports the best results on the cross-modal visual-textual matching task using deep neural networks equipped with cross-attention mechanisms. However, most of these methods cannot produce compact indexable features, posing challenging scalability issues when working with large volumes of data. This presentation will discuss the work carried out in collaboration with the VIPER laboratory at the University of Geneva. I dealt with multi-modal feature extraction proposing a state-of-the-art self-attentive architecture, and I began exploring different methods to sparsify the obtained features for making them indexable.

Luca Pappalardo - The relationship between human mobility and viral transmissibility during the COVID-19 epidemics in Italy

Abstract: In 2020, countries affectedby the COVID-19 pandemic implemented various non-pharmaceutical interventions to contrast the spread of the virus and its impact on their healthcare systems and economies. Using Italian data at different geographic scales, we investigate the relationship between human mobility, which subsumes many facets of the population's response to the changing situation, and the spread of COVID-19. Leveraging mobile phone data from February through September 2020, we find a striking relationship between the decrease in mobility flows and the net reproduction number (the Rt). We find that the time needed to switch off mobility and bring the net reproduction number below the critical threshold of 1 is about one week. Moreover, we observe a strong relationship between the number of days spent above such threshold before the lockdown-induced drop inmobility flows and the total number of infections per 100k inhabitants. Estimating the statistical effect of mobility flows on the net reproduction number overtime, we document a 2-week lag positive association, strong in March and April, and weaker but still significant in June.  Our study demonstrates the value of big mobility data to monitor the epidemic and inform control nterventions during its unfolding.


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